Feature Selective Projection with Low-Rank Embedding and Dual Laplacian Regularization.
Chang TangXinwang LiuXinzhong ZhuJian XiongMiaomiao LiJingyuan XiaXiangke WangLizhe WangPublished in: IEEE Trans. Knowl. Data Eng. (2020)
Keyphrases
- low rank
- rank minimization
- trace norm
- minimization problems
- matrix factorization
- convex optimization
- high order
- linear combination
- group sparsity
- kernel matrices
- missing data
- high dimensional data
- singular value decomposition
- kernel matrix
- matrix completion
- rank constraint
- low rank matrix
- semi supervised
- sparse coding
- matrix decomposition
- low rank matrices
- graph laplacian
- data sets
- regularized regression
- manifold structure
- primal dual
- norm minimization
- singular values
- feature vectors
- affinity matrix
- non rigid structure from motion
- reproducing kernel hilbert space